MUMBAI, India, Aug. 31 -- Intellectual Property India has published a patent application (202641099076 A) filed by Pawan Maheshwari on August 17, 2026, for Ai Harmonic Ethical Index (ahei).
Inventors include Pawan Maheshwari; and Bhavin Maheshwari.
The application for the patent was published on August 28, 2026, under issue no. 35/2026.
Abstract: A system and method for evaluating the ethical alignment of artificial-intelligence artefacts — including user prompts, AI models, and AI providers — and for rendering the evaluation simultaneously as (i) a non-linear Fibonacci-quantised magnitude score and (ii) a psychoacoustically meaningful harmonic (musical) profile. Input artefacts are scored across a plurality of ethical dimensions (e.g., harm avoidance, fairness, privacy, honesty, autonomy, legality for prompts; weight openness, licence permissiveness, documentation, safety framework, data transparency for providers). Dimension scores are combined by an ethically weighted mean and quantised onto the Fibonacci sequence {1, 2, 3, 5, 8, 13, 21} through a monotone band-transfer function whose widening gaps encode increasing difficulty of ethical improvement and suppress false precision. In parallel, each dimension score is mapped to a musical interval relative to a root frequency — consonant intervals (octave, perfect fifth, major third) for high alignment, dissonant intervals (minor second, tritone) for violations — and the resulting intervals are stacked into an audible chord via a real-time synthesis engine, such that ethically sound artefacts produce stable, consonant chords and problematic artefacts audibly “grind.” The magnitude (Fibonacci band) and the profile (chord) together constitute a combined ethical signature, the AI Resonance Fingerprint. The system further comprises an explainability engine that decomposes every score against a published rubric with per-dimension improvement levers; a harmonic drift detector that compares signatures across model versions; a governance comparison engine that positions results against jurisdictional AI-governance regimes (EU, US, China, UK, India); a prompt-optimisation engine; and a reference deep-learning pipeline in which a transformer encoder with per-dimension regression heads reproduces the transparent rubric from public artefacts. Applications include enterprise AI governance, regulatory compliance, procurement, education, and AI auditing.
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